Analyzing and visualizing data

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Computer Science

analyzing and visualizing data

University of cumberlands

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Build a summary of the text book Analyzing and visualizing data by A. Kirk, chapter 1-11. You can reuse the chapter summary slides (attached)- identify the key learning points of each chapter - the best visualization techniques you learnt from the material.

A good powerpoint presentation will have 10-20 slides. Reuse the attached powerpoint slides for the template -

Take advantage of the accompanying website http://book.visualisingdata.com/home and focus best visualizations Jan - Jun 2018:

http://www.visualisingdata.com/2018/08/10-signific...

Also remember to put your first and last name, email address and student id on the front slide.

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School of Computer & Information Sciences ITS530 Analyzing and Visualizing Data Summary 10/9/2018 Analyzing and Visualizing Data Summary 1 Kirk, A. (2016). Data Visualisation: A Handbook for Data Driven Design. Thousand Oaks, CA: Sage Publications, Ltd. ISBN: 978-1-47391214-4 Stage 1 Stage 2 Stage 3 Stage 4 Formulati ng your Working with Develop your Brief Data Establish your Editorial Thinking 10/9/2018 Design Solution Chapter 1 Defining data visualisation Chapter 2 Visualisation workflow Chapter 3 Formulating your brief Chapter 4 Working with data Chapter 5 Establishing your editorial thinking Chapter 6 Data representation Chapter 7 Interactivity Chapter 8 Annotation Chapter 9 Colour Chapter 10 Composition Chapter 11 Visualisation literacy Analyzing and Visualizing Data Summary 2 Chapter 1 Defining Data Visualization ➢ Definition for Data Visualization • Data • Representation • Presentation • Understanding ➢ Process of Understanding • Perceiving • Interpreting • Comprehending 10/9/2018 ➢ Principles of Good Visualization Design 1. Trustworthy • Trust vs Truth • Trust Applies Throughout the Process 2. Accessible • Useful • Understandable • Unobtrusive 3. Elegant • Aesthetic • Thorough to last detail • As little design as pssible Analyzing and Visualizing Data Summary 3 Chapter 2 Visualization Workflow ➢ Four Stages of the Visualization Workflow • Formulating your brief • Working with data • Establishing your editorial thinking • Developing your design solution ➢ Formulating your brief: • • • Planning Defining Initiating your project ➢ Working with data: • • Going through the mechanics of gathering Handling and preparing your data ➢ Establishing your Editorial Thinking Stage 1 Stage 2 Stage 3 Stage 4 Formulati ng your Working with Develop your Brief Data Establish your Editorial Thinking 10/9/2018 Design Solution • Defining what you will show your audience. ➢ Developing your design solution: • • Considering all the design options Beginning the production cycle. Analyzing and Visualizing Data Summary 4 Chapter 3 Formulating your Brief ➢ What is a Brief? ➢ Establish your Project’s Vision • A brief represents a set of expectations and • Curiosity, circumstances, consumption, captures all the relevant information about a task deliverables establish the purpose map or project • Use “The Purpose Map” ➢ Establish your Projects Context • The best fit solution to facilitate the • Curiosity/Intrigue: personal, stakeholder, desired purpose! • • • audience, anticipated, potential intrigue Circumstances • People – Stakeholders, audience • Constraints – Pressures, rules Consumption (Frequency, Setting) Deliverables (Quantity, Format, Skills, Technology) • • Experience (Explanatory, Exhibitory, Exploratory) Tone (Reading, Feeling) ➢ Defining your Projects Purpose 10/9/2018 Analyzing and Visualizing Data Summary 5 Chapter 4 Working with Data ➢ Data Assets and Tabulation Types ➢ Data Transformation • Qualitative (Textual, Nominal, Ordinal) • Nominal (e.g. Gender) Ordinal (e.g. Survey Q. 1-5) • Quantitative (Interval, Ratio) ➢ Data Acquisition (different sources) • Clean: Resolve data quality • Create: New calculations, conversions • Consolidate Any other data? ➢ Data Exploration • Curated by you • Curated by others (downloaded from web, ) ➢ Data Examination • Visual and Statistical Techniques • See data quality • Insights? • Physical properties: Type, size, condition, age • Meaning: Phenomenon, completeness 10/9/2018 Analyzing and Visualizing Data Summary 6 Chapter 5 Establish your Editorial Thinking ➢ Angle ➢ Focus • Must be relevant in its potential interest for your audience. • Must have sufficient quantities to cover all relevant views – but no more than required. • Which features of the display to draw particular attention to? • How to organize the visibility and hierarchy of the content? ➢ Framing • Applying filters to your data to determine the inclusion and exclusion criteria. • Framing decisions must provide access to the most salient content but also avoid any distorting of the view of the data. 10/9/2018 Analyzing and Visualizing Data Summary 7 Chapter 6 Data Representation ➢ Introducing Visual Encoding • All Charts based on Marks and Attributes • Marks represent records for aggregation • Points, lines, areas, shapes, forms • Attributes • Variable values held for each record • Properties: Size, color, connection ➢ Chart Types • Visual encoding is fundamental • Chart types are practical application 10/9/2018 ➢ Five Families of Chart Types • • • • • Categorical Hierarchical Relational Temporal Spatial ➢ Data Visualization Workflow 1. 2. 3. 4. Analyzing and Visualizing Data Summary Formulate your brief Work with Data Establish Editorial Thinking Develop Design • • • Trustworthy Design Accessible Design Elegant Design 8 Chapter 7 Interactivity ➢ Data Adjustments affect what is displayed ➢ Data Visualization Workflow • • • • • 1. 2. 3. 4. Framing, Navigating, Animating, Sequencing, Customizing • • • ➢ Presentation Adjustments • • • Focusing, Annotating, Orientating 10/9/2018 Formulate your brief Work with Data Establish Editorial Thinking Develop Design Solution Trustworthy Design Accessible Design Elegant Design Stage 1 Stage 2 Stage 3 Stage 4 Formulati ng your Working with Develop your Brief Data Establish your Editorial Thinking Analyzing and Visualizing Data Summary Design Solution 9 Chapter 8 Annotation ➢ Chart Annotations ➢ Project Annotations helps viewers • Understand project purpose, usage; may include: • Headings, titles, sub-titles, section headings • Introductions: background, aims of the project • User guides: advice or instructions on how to use • Multimedia: add images, videos or illustrations • Footnotes: potentially include data sources, credits, time/date, usage info, references Stage 1 Stage 2 Stage 3 Stage 4 Formulati ng your Working with Develop your Brief Data Establish your Editorial Thinking • • • • • • Chart Apparatus: axis lines, grid lines, tick marks Labels: axis labels, value labels Legend: detailed keys for color or size associations Reading guides: instructions on how to read chart Captions: drawing out key findings Typography: choice of font-size hierarchy, legibility of type Design Solution ITS530 Chapter 8 10 Chapter 9 Color “Chapter Overview” ➢ Color design decision - most immediate impact! • Key: Meaning first and decoration second ➢ 9.1 Overview of Color Theory • RGB – Red, Green Blue – form screen colors • CMYK – Cyan, Magenta, Yellow, Black - print • Hue – the true color • Saturation – colorfulness of Hue • Lightness contrast of a different Hue • Other models (HSV, HSI, HSB, HCL) ➢ Features of Color: Data Legibility • Data Legibility • Editorial Salience • Functional Harmony ➢ Data Legibility • • • Nominal (Qualitative) Ordinal (Qualitative) Interval & Ratio (Quantitative) ➢ 9.3 Editorial Salience ➢ 9.4 Functional Harmony • Interactive features, annotation, composition ➢ 9.5 Visualization Workflow Stage 1 Stage 2 Stage 3 Stage 4 Formulati ng your Working with Develop your Brief Data Establish your Editorial Thinking ITS530 Chapter 9 Design Solution 11 Chapter 10 Composition ➢ Features of Composition • Project Composition • Chart Composition ➢ 10.1 Project Composition • Wireframing or storyboarding • Wireframing involves sketching the layout and size of all the major content across a single-page view • Storyboarding is when you want to establish a high level feel for the overall architecture of content. ➢ 10.2 Chart Composition • • • • • • Chart Size Chart Scales Chart Orientation Chart Value Sorting Ordinal (Qualitative) Interval & Ratio (Quantitative) Stage 1 Stage 2 Stage 3 Stage 4 Formulati ng your Working with Develop your Brief Data Establish your Editorial Thinking ITS530 Chapter 10 Design Solution 12 Chapter 11 Visualization Literacy ➢ Capabilities of the Visualizer ➢ Before you begin 1. Initiator – overseas the project • Setting, Visual Appeal, Relevance 2. Data Scientist - the data miner • Initial Scan? 3. Journalist is the storyteller ➢ Outside the Chart 4. Computer Scientist is the executor • The proposition – Format, Shape and Size 5. Designer is the creative one • What is the project about 6. Cognitive Scientist is the thinker • What Data? 7. Communicator is the negotiator 8. the Project manager • Interactive Function? http://www.visualisingdata.com/2012/06/article-the-8-hats-of-data➢ Inside the Chart • Perceiving – Comprehending - Understanding ➢ A More Sophisticated Consumer • • Appreciation of context, Overview then details visualisation-design/ Stage 1 Stage 2 Stage 3 Stage 4 Formulati ng your Working with Develop your Brief Data Establish your Editorial Thinking ITS530 Chapter 11 Design Solution 13 Questions? 10/9/2018 Analyzing and Visualizing Data Summary 14
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Analyzing and visualizing data
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Defining Data Visualization
 This chapter is based on creating and studying of the visual representation






of data.
In order to be able to communicate clearly and efficiently, data
visualization must make use of statistical graphics, information graphics,
plots, as well as other tools.
Visualization of information effectively makes it possible to analyze and
reason about data and evidence.
To understand data visualization, it is important to perceive, interpret, and
comprehend it.
The chapter also talks about the principles of a good visualization design,
which include trustworthy, accessible, and elegant.

Visualization Workflow
 In this chapter, we get to know the different stages of visualization workflow.
 The different stages include brief formulation, working with data, editorial





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